Title :
Graph-based methods for Horn knowledge compression
Author :
Hammer, Peter L. ; Kogan, Alexander
Author_Institution :
RUTCOR, Rutgers Univ., New Brunswick, NJ, USA
Abstract :
Horn knowledge bases are widely used in many applications. The paper is concerned with the optimal compression of propositional Horn production rule bases/spl minus/one of the most important knowledge bases used in practice. The problem of knowledge compression is interpreted as a problem of Boolean function minimization. It was proved by P.L. Hammer and A. Kogan (1993) that the minimization of Horn functions, i.e. Boolean functions associated to Horn knowledge bases, is NP-complete. The paper deals with the minimization of quasi-acyclic Horn functions, the class of which properly includes the two practically significant classes of quadratic and of acyclic functions. A procedure is developed for recognizing in quadratic time the quasi-acyclicity of a function given by a Horn CNF, and a graph-based algorithm is proposed for the quadratic time minimization of quasi-acyclic Horn functions.<>
Keywords :
Boolean functions; Horn clauses; data compression; graph theory; knowledge based systems; minimisation; Boolean function minimization; Horn CNF; Horn knowledge bases; Horn knowledge compression; NP-complete; acyclic functions; conjunctive normal form; graph-based algorithm; graph-based methods; knowledge compression; optimal compression; propositional Horn production rule bases; quadratic time minimization; quasi-acyclic Horn functions;
Conference_Titel :
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
0-8186-5090-7
DOI :
10.1109/HICSS.1994.323341